15+ Machine/Deep Learning Projects in Ipython Notebooks
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Updated
Apr 3, 2020 - Jupyter Notebook
15+ Machine/Deep Learning Projects in Ipython Notebooks
pwtools is a Python package for pre- and postprocessing of atomistic calculations, mostly targeted to Quantum Espresso, CPMD, CP2K and LAMMPS. It is almost, but not quite, entirely unlike ASE, with some tools extending numpy/scipy. It has a set of powerful parsers and data types for storing calculation data.
A repository to explore the concepts of applied econometrics in the context of financial time-series.
This repo demonstrates how to build a surrogate (proxy) model by multivariate regressing building energy consumption data (univariate and multivariate) and use (1) Bayesian framework, (2) Pyomo package, (3) Genetic algorithm with local search, and (4) Pymoo package to find optimum design parameters and minimum energy consumption.
Iterative hard thresholding for l0 penalized regression
SKBEL - Bayesian Evidential Learning framework built on top of scikit-learn.
Code to perform multivariate linear regression using Gibbs sampling
Several examples of multivariate techniques implemented in R, Python, and SAS. Multivariate concrete dataset retrieved from https://archive.ics.uci.edu/ml/datasets/Concrete+Slump+Test. Credit to Professor I-Cheng Yeh.
MATLAB implementation of Gradient Descent algorithm for Multivariate Linear Regression
Building a logistic regression model for telecom churn prediction, utilizing 21 customer-related variables to predict whether a customer will switch to another telecom provider or not.
Equities Pair Trading/Statistical Arbitrage and Multi-Variable Index Regression
A small tutorial on MARS: Multivariate Adaptive Regression Splines in Python
python implementation of process mining and machine learning algorithm
The project aims to perform various visualizations and provide various insights from the considered Indian automobile dataset by performing data analysis that utilizing machine learning algorithms in R programming language.
Multivariate Markov-Switching Models Regressions Framework
A graphical multivariate lesion-symptom mapping toolbox
A cluster of Machine Learning algorithms
Helper R scripts for multiple PERMANOVA tests, AICc script for PERMANOVA, etc.
Forecasting exchange rates by using commodities prices
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